On quantifying the apparent temperature sensitivity of plant phenology.

Many plant phenological events are sensitive to temperature, leading to changes in the seasonal cycle of ecosystem function as the climate warms. To evaluate the current and future implications of temperature changes for plant phenology, researchers commonly use a metric of temperature sensitivity, which quantifies the change in phenology per degree change in temperature. Here, we examine the temperature sensitivity of phenology, and highlight conditions under which the widely used days-per-degree sensitivity approach is subject to methodological issues that can generate misleading results. We identify several factors, in particular the length of the period over which temperature is integrated, and changes in the statistical characteristics of the integrated temperature, that can affect the estimated apparent sensitivity to temperature. We show how the resulting artifacts can lead to spurious differences in apparent temperature sensitivity and artificial spatial gradients. Such issues are rarely considered in analyses of the temperature sensitivity of phenology. Given the issues identified, we advocate for process-oriented modelling approaches, informed by observations and with fully characterised uncertainties, as a more robust alternative to the simple days-per-degree temperature sensitivity metric. We also suggest approaches to minimise and assess spurious influences in the days-per-degree metric

Leaf age effects on the spectral predictability of leaf traits in Amazonian canopy trees

Recent work has shown that leaf traits and spectral properties change through time and/or seasonally as leaves age. Current field and hyperspectral methods used to estimate canopy leaf traits could, therefore, be significantly biased by variation in leaf age. To explore the magnitude of this effect, we used a phenological dataset comprised of leaves of different leaf age groups -developmental, mature, senescent and mixed-age- from canopy and emergent tropical trees in southern Peru. We tested the performance of partial least squares regression models developed from these different age groups when predicting traits for leaves of different ages on both a mass and area basis. Overall, area-based models outperformed mass-based models with a striking improvement in prediction observed for area-based leaf carbon (Carea) estimates. We observed trait-specific age effects in all mass-based models while area-based models displayed age effects in mixed-age leaf groups for Parea and Narea. Spectral coefficients and variable importance in projection (VIPs) also reflected age effects. Both mass- and area-based models for all five leaf traits displayed age/temporal sensitivity when we tested their ability to predict the traits of leaves of other age groups. Importantly, mass based mature models displayed the worst overall performance when predicting the traits of leaves from other age groups. These results indicate that the widely adopted approach of using fully expanded mature leaves to calibrate models that estimate remotely-sensed tree canopy traits introduces error that can bias results depending on the phenological stage of canopy leaves. To achieve temporally stable models, spectroscopic studies should consider producing area-based estimates as well as calibrating models with leaves of different age groups as they present themselves through the growing season. We discuss the implications of this for surveys of canopies with synchronised and unsynchronised leaf phenology

Influence of ENSO and the NAO on terrestrial carbon uptake in the Texas-northern Mexico region

Climate extremes such as drought and heat waves can cause substantial reductions in terrestrial carbon uptake. Advancing projections of the carbon uptake response to future climate extremes depends on (1) identifying mechanistic links between the carbon cycle and atmospheric drivers, (2) detecting and attributing uptake changes, and (3) evaluating models of land response and atmospheric forcing. Here, we combine model simulations, remote sensing products, and ground observations to investigate the impact of climate variability on carbon uptake in the Texas‐northern Mexico region. Specifically, we (1) examine the relationship between drought, carbon uptake, and variability of El Niño–Southern Oscillation (ENSO) and the North Atlantic Oscillation (NAO) using the Joint UK Land‐Environment Simulator (JULES) biosphere simulations from 1950–2012, (2) quantify changes in carbon uptake during record drought conditions in 2011, and (3) evaluate JULES carbon uptake and soil moisture in 2011 using observations from remote sensing and a network of flux towers in the region. Long‐term simulations reveal systematic decreases in regional‐scale carbon uptake during negative phases of ENSO and NAO, including amplified reductions of gross primary production (GPP) (−0.42 ± 0.18 Pg C yr^(−1)) and net ecosystem production (NEP) (−0.14 ± 0.11 Pg C yr^(−1)) during strong La Niña years. The 2011 megadrought caused some of the largest declines of GPP (−0.50 Pg C yr^(−1)) and NEP (−0.23 Pg C yr^(−1)) in our simulations. In 2011, consistent declines were found in observations, including high correlation of GPP and surface soil moisture (r = 0.82 ± 0.23, p = 0.012) in remote sensing‐based products. These results suggest a large‐scale response of carbon uptake to ENSO and NAO, and highlight a need to improve model predictions of ENSO and NAO in order to improve predictions of future impacts on the carbon cycle and the associated feedbacks to climate change

Nitrogen and phosphorus constrain the CO2 fertilization of global plant biomass

Unidad de excelencia María de Maeztu MdM-2015-0552Elevated CO2 (eCO2) experiments provide critical information to quantify the effects of rising CO2 on vegetation. Many eCO2 experiments suggest that nutrient limitations modulate the local magnitude of the eCO2 effect on plant biomass but the global extent of these limitations has not been empirically quantified, complicating projections of the capacity of plants to take up CO2. Here, we present a data-driven global quantification of the eCO2 effect on biomass based on 138 eCO2 experiments. The strength of CO2 fertilization is primarily driven by nitrogen (N) in ~65% of global vegetation and by phosphorus (P) in ~25% of global vegetation, with N- or P-limitation modulated by mycorrhizal association. Our approach suggests that CO2 levels expected by 2100 can potentially enhance plant biomass by 12 ± 3% above current values, equivalent to 59 ± 13 PgC. The global-scale response to eCO2 we derive from experiments is similar to past changes in greenness and biomass10 with rising CO2, suggesting that CO2 will continue to stimulate plant biomass in the future despite the constraining effect of soil nutrients. Our research reconciles conflicting evidence on CO2 fertilization across scales and provides an empirical estimate of the biomass sensitivity to eCO2 that may help to constrain climate projections

Developing an intervention to facilitate family communication about inherited genetic conditions, and training genetic counsellors in its delivery.

Many families experience difficulty in talking about an inherited genetic condition that affects one or more of them. There have now been a number of studies identifying the issues in detail, however few have developed interventions to assist families. The SPRinG collaborative have used the UK Medical Research Council's guidance on Developing and Evaluating Complex Interventions, to work with families and genetic counsellors (GCs) to co-design a psycho-educational intervention to facilitate family communication and promote better coping and adaptation to living with an inherited genetic condition for parents and their children (<18 years). The intervention is modelled on multi-family discussion groups (MFDGs) used in psychiatric settings. The MFDG was developed and tested over three phases. First focus groups with parents, young people, children and health professionals discussed whether MFDG was acceptable and proposed a suitable design. Using evidence and focus group data, the intervention and a training manual were developed and three GCs were trained in its delivery. Finally, a prototype MFDG was led by a family therapist and co-facilitated by the three GCs. Data analysis showed that families attending the focus groups and intervention thought MFDG highly beneficial, and the pilot sessions had a significant impact on their family' functioning. We also demonstrated that it is possible to train GCs to deliver the MFDG intervention. Further studies are now required to test the feasibility of undertaking a definitive randomised controlled trial to evaluate its effectiveness in improving family outcomes before implementing into genetic counselling practice.The National Institute of Health Research funded the study but any views expressed do not necessarily reflect those of the Authority. Funded by NIHR reference number: RP-DG-1211-10015

Tracking vegetation phenology across diverse North American biomes using PhenoCam imagery

Vegetation phenology controls the seasonality of many ecosystem processes, as well as numerous biosphere-atmosphere feedbacks. Phenology is also highly sensitive to climate change and variability. Here we present a series of datasets, together consisting of almost 750 years of observations, characterizing vegetation phenology in diverse ecosystems across North America. Our data are derived from conventional, visible-wavelength, automated digital camera imagery collected through the PhenoCam network. For each archived image, we extracted RGB (red, green, blue) colour channel information, with means and other statistics calculated across a region-of-interest (ROI) delineating a specific vegetation type. From the high-frequency (typically, 30 min) imagery, we derived time series characterizing vegetation colour, including “canopy greenness”, processed to 1- and 3-day intervals. For ecosystems with one or more annual cycles of vegetation activity, we provide estimates, with uncertainties, for the start of the “greenness rising” and end of the “greenness falling” stages. The database can be used for phenological model validation and development, evaluation of satellite remote sensing data products, benchmarking earth system models, and studies of climate change impacts on terrestrial ecosystems

Age, allocation and availability of nonstructural carbon in mature red maple trees

The allocation of nonstructural carbon (NSC) to growth, metabolism and storage remains poorly understood, but is critical for the prediction of stress tolerance and mortality. We used the radiocarbon (14C) ‘bomb spike’ as a tracer of substrate and age of carbon in stemwood NSC, CO2 emitted by stems, tree ring cellulose and stump sprouts regenerated following harvesting in mature red maple trees. We addressed the following questions: which factors influence the age of stemwood NSC?; to what extent is stored vs new NSC used for metabolism and growth?; and, is older, stored NSC available for use? The mean age of extracted stemwood NSC was 10 yr. More vigorous trees had both larger and younger stemwood NSC pools. NSC used to support metabolism (stem CO2) was 1–2 yr old in spring before leaves emerged, but reflected current-year photosynthetic products in late summer. The tree ring cellulose 14C age was 0.9 yr older than direct ring counts. Stump sprouts were formed from NSC up to 17 yr old. Thus, younger NSC is preferentially used for growth and day-to-day metabolic demands. More recently stored NSC contributes to annual ring growth and metabolism in the dormant season, yet decade-old and older NSC is accessible for regrowth

Carbon budget of the Harvard Forest Long- Term Ecological Research site: pattern, process, and response to global change

How, where, and why carbon (C) moves into and out of an ecosystem through time are long- standing questions in biogeochemistry. Here, we bring together hundreds of thousands of C- cycle observations at the Harvard Forest in central Massachusetts, USA, a mid- latitude landscape dominated by 80- 120- yr- old closed- canopy forests. These data answered four questions: (1) where and how much C is presently stored in dominant forest types; (2) what are current rates of C accrual and loss; (3) what biotic and abiotic factors contribute to variability in these rates; and (4) how has climate change affected the forest- s C cycle? Harvard Forest is an active C sink resulting from forest regrowth following land abandonment. Soil and tree biomass comprise nearly equal portions of existing C stocks. Net primary production (NPP) averaged 680- 750 g C·m- 2·yr- 1; belowground NPP contributed 38- 47% of the total, but with large uncertainty. Mineral soil C measured in the same inventory plots in 1992 and 2013 was too heterogeneous to detect change in soil- C pools; however, radiocarbon data suggest a small but persistent sink of 10- 30 g C·m- 2·yr- 1. Net ecosystem production (NEP) in hardwood stands averaged ~300 g C·m- 2·yr- 1. NEP in hemlock- dominated forests averaged ~450 g C·m- 2·yr- 1 until infestation by the hemlock woolly adelgid turned these stands into a net C source. Since 2000, NPP has increased by 26%. For the period 1992- 2015, NEP increased 93%. The increase in mean annual temperature and growing season length alone accounted for ~30% of the increase in productivity. Interannual variations in GPP and NEP were also correlated with increases in red oak biomass, forest leaf area, and canopy- scale light- use efficiency. Compared to long- term global change experiments at the Harvard Forest, the C sink in regrowing biomass equaled or exceeded C cycle modifications imposed by soil warming, N saturation, and hemlock removal. Results of this synthesis and comparison to simulation models suggest that forests across the region are likely to accrue C for decades to come but may be disrupted if the frequency or severity of biotic and abiotic disturbances increases.Peer Reviewedhttp://deepblue.lib.umich.edu/bitstream/2027.42/163495/3/ecm1423_am.pdfhttp://deepblue.lib.umich.edu/bitstream/2027.42/163495/2/ecm1423-sup-0001-AppendixS1.pdfhttp://deepblue.lib.umich.edu/bitstream/2027.42/163495/1/ecm1423.pd

Thinning Can Reduce Losses in Carbon Use Efficiency and Carbon Stocks in Managed Forests Under Warmer Climate

Forest carbon use efficiency (CUE, the ratio of net to gross primary productivity) represents the fraction of photosynthesis that is not used for plant respiration. Although important, it is often neglected in climate change impact analyses. Here we assess the potential impact of thinning on projected carbon cycle dynamics and implications for forest CUE and its components (i.e., gross and net primary productivity and plant respiration), as well as on forest biomass production. Using a detailed process-based forest ecosystem model forced by climate outputs of five Earth System Models under four representative climate scenarios, we investigate the sensitivity of the projected future changes in the autotrophic carbon budget of three representative European forests. We focus on changes in CUE and carbon stocks as a result of warming, rising atmospheric CO2 concentration, and forest thinning. Results show that autotrophic carbon sequestration decreases with forest development, and the decrease is faster with warming and in unthinned forests. This suggests that the combined impacts of climate change and changing CO2 concentrations lead the forests to grow faster, mature earlier, and also die younger. In addition, we show that under future climate conditions, forest thinning could mitigate the decrease in CUE, increase carbon allocation into more recalcitrant woody pools, and reduce physiological-climate-induced mortality risks. Altogether, our results show that thinning can improve the efficacy of forest-based mitigation strategies and should be carefully considered within a portfolio of mitigation options